EE 359: Wireless Communications
Professor Andrea Goldsmith
Outline
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Course Basics
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Course Syllabus
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The Wireless Vision
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Technical Challenges
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Current Wireless Systems
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Spectrum Regulation and Standards
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Emerging Wireless Systems
Course Information*
People
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Instructor: Andrea Goldsmith, andrea@ee, Packard
371, OHs: MW after class and by appt.
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TAs: Mainak Chowdhury, mainakch@stanford.edu,
and Milind Rao, milind@stanford.edu,
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Discussion Tues 4-5 pm (televised) or 5-6pm
OHs: Tues after discussion (Mainak), Wed 5-6pm, Thur
9:30-10:30 (Milind), location TBA.
Email OHs (ideally via Piazza): Thursday 2-4 pm. Piazza
website: https://piazza.com/stanford/fall2014/ee359/home
Class Administrator: Pat Oshiro, poshiro@stanford,
Packard 365, 3-2681. Homework dropoff: Th by 5 pm.
*See web or handout for more details
Course Information
Nuts and Bolts
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Prerequisites: EE279 or equivalent (Digital Communications)
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Required Textbook: Wireless Communications (by me), CUP
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Class Homepage: www.stanford.edu/class/ee359
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Available at bookstore (out of stock) or Amazon
Extra credit for finding typos/mistakes/suggestions (2nd ed. soon!)
Supplemental texts on 1 day reserve at Engineering Library.
All handouts, announcements, homeworks, etc. posted to website
“Lectures” link continuously updates topics, handouts, and reading
Class Mailing List: ee359-aut1415-students@lists (automatic
for on-campus registered students).
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Guest list ee359-aut1415-guest@lists for SCPD and auditors: send
Mainak/Milind email to sign up.
Sending mail to ee359-aut1415-staff@lists reaches me and TAs.
Course Information
Policies
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Grading: Two Options
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HWs: assigned Thurs, due following Thurs 5pm (starts 9/25)
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No Project (3 units): HW – 30%, 2 Exams – 30%, 40%
Project (4 units): HWs- 20%, Exams - 25%, 30%, Project - 25%
Homeworks lose 33% credit per day late, lowest HW dropped
Up to 3 students can collaborate and turn in one HW writeup
Collaboration means all collaborators work out all problems together
Unpermitted collaboration or aid (e.g. solns for the book or from prior
years) is an honor code violation and will be dealt with strictly.
Exams:
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Midterm week of 11/3. (It will be scheduled outside class time; the
duration is 2 hours.) Final on 12/8 from 8:30-11:30 am.
Exams must be taken at scheduled time, unless a course conflicts
Course Information
Projects
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The term project (for students electing to do a project) is a
research project related to any topic in wireless
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Two people may collaborate if you convince me the sum of
the parts is greater than each individually
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A 1 page proposal is due 10/24 at 5 pm.
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The project is due by 5 pm on 12/6 (on website)
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5-10 hours of work typical for proposal
Project website must be created and proposal posted there
20-40 hours of work after proposal is typical for a project
Suggested topics in project handout
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Anything related to wireless or application of wireless techniques ok.
Course Syllabus
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Overview of Wireless Communications
Path Loss, Shadowing, and Fading Models
Capacity of Wireless Channels
Digital Modulation and its Performance
Adaptive Modulation
Diversity
MIMO Systems
Multicarrier Modulation
Spread Spectrum
Intro to Wireless Networks (EE360)
Lecture #
Date
Topic
Required Reading
Introduction
1
9/22
Overview of Wireless Communications
Chapter 1 and Appendix D
Wireless Channel Models
2*-3
9/26*,9/29
4-5
10/1,10/6
6
10/8
Path Loss and Shadowing Models
Statistical Fading Models, Narrowband Fading
Wideband Fading Models
Lec 2: Section 2.1 to 2.6
Lec 3: Section 2.7 to 2.10
Lec 4: Section 3.1 to 3.2.1
Lec 5: Section 3.1 to 3.2
Section 3.2 to 3.3
Impact of Fading and ISI on Wireless Performance
7
8,9*,10
10/13
10/15,10/22,
10/24*
Capacity of Wireless Channels
Digital Modulation and its Performance
Chapter 4
Lec 8: Chapter 5
Lec 9-10: Chapter 6
Flat-Fading Countermeasures
11
12
10/27
10/29
MT
Week of 11/3
13
11/3
14,15,16*
17
18
Diversity
Adaptive Modulation
Midterm (outside class time)
Practical Considerations in Adaptive Modulation
11/5,11/10, 11/17 Multiple Input/Output Systems (MIMO)
11/19
11/21*
ISI Countermeasures
Equalization, Multicarrier Systems
Multicarrier Modulation and OFDM
Chapter 7
Section 9.1 to 9.2
Chapters 2 to 7
Section 9.3
Chapter 10 & Appendix C
Chapter 12.1-12.3
Chapter 12.4-12.6
Multiuser Systems
19
12/1
20
12/3
Final
12/8
Spread Spectrum and CDMA
Overview of multiuser systems & networks
Course summary
8:30-11:30 am
No lectures Wed 9/24, Mon 10/20, Wed 11/12
Chapter 13
Sections 14.1 to 14.4, 15.1 to 15.2,
16.1 to 16.3
Class Rescheduling
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9/24 (this Wed) moved to 9/26 (this Fri), 9:30-10:45,
102 Thornton (w/donuts)
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10/20 (Mon) rescheduled to Fri 10/24, tentatively
9:30-10:45am, 102 Thornton (w/donuts)
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11/12 (Wed) rescheduled to Fri 11/21, tentatively
9:30-10:45am, 102 Thornton (w/donuts)
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May have optional advanced topics lecture the last
week of classes (evening or lunch, w/ pizza)
Wireless History
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Ancient Systems: Smoke Signals, Carrier Pigeons, …
Radio invented in the 1880s by Marconi
Many sophisticated military radio systems were
developed during and after WW2
Cellular has enjoyed exponential growth since
1988, with almost 5 billion users worldwide today
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Ignited the wireless revolution
Voice, data, and multimedia ubiquitous
Use in third world countries growing rapidly
Wifi also enjoying tremendous success and growth
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Wide area networks (e.g. Wimax) and short-range
systems other than Bluetooth (e.g. UWB) less successful
Future Wireless Networks
Ubiquitous Communication Among People and Devices
Next-generation Cellular
Wireless Internet Access
Wireless Multimedia
Sensor Networks
Smart Homes/Spaces
Automated Highways
In-Body Networks
All this and more …
Challenges
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Network Challenges
Scarce/bifurcated spectrum
 Demanding/diverse applications
 Heterogeneous networks
 High-performance requirements
 Reliability and coverage
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Device Challenges
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Size, Power, Cost
Multiple Antennas in Silicon
Multiradio Integration
Coexistance
BT
Cellular
FM/XM
GPS
DVB-H
Apps
Processor
WLAN
Media
Processor
Wimax
Software-Defined (SD) Radio:
Is this the solution to the device challenges?
BT
Cellular
FM/XM
GPS
DVB-H
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A/D
Apps
Processor
WLAN
Media
Processor
Wimax
A/D
A/D
DSP
A/D
Wideband antennas and A/Ds span BW of desired signals
DSP programmed to process desired signal: no specialized HW
Today, this is not cost, size, or power efficient
Compressed sensing may be a solution for sparse signals
Current Wireless Systems
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Cellular Systems
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Wireless LANs
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WiGig and mmWave Communications
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Cognitive Radios
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Satellite Systems
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Zigbee radios
Driving Constraint in Wireless
System Design: Scarce Spectrum
$$$
Licensed Bands Scarce & Expensive
Spectral Reuse
Due to its scarcity, spectrum is reused
In licensed bands
and unlicensed bands
BS
Cellular
Wifi, BT, UWB,…
Reuse introduces interference
Cellular Systems:
Reuse channels to maximize capacity
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Geographic region divided into cells
Frequency/timeslots/codes reused at spatially-separated locations.
Co-channel interference between same color cells (reuse 1 common now).
Base stations/MTSOs coordinate handoff and control functions
Shrinking cell size increases capacity, as well as networking burden
BASE
STATION
MTSO
Future Cellular Phones
Burden
for this
performance
is on the backbone network
Everything
wireless
in one device
San Francisco
BS
BS
LTE backbone is the Internet
Internet
Nth-Gen
Cellular
Phone
System
Nth-Gen
Cellular
Paris
BS
Much better performance and reliability than today
- Gbps rates, low latency, 99% coverage indoors and out
4G/LTE Cellular
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Much higher data rates than 3G (50-100 Mbps)
 3G
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systems has 384 Kbps peak rates
Greater spectral efficiency (bits/s/Hz)
 More
bandwidth, adaptive OFDM-MIMO,
reduced interference
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Flexible use of up to 100 MHz of spectrum
 20
MHz spectrum allocation common
Low packet latency (<5ms).
 Reduced cost-per-bit
 All IP network
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Careful what you wish for…
Source: FCC
Source: Unstrung Pyramid Research 2010
Growth in mobile data, massive spectrum deficit and stagnant revenues
require technical and political breakthroughs for ongoing success of cellular
20
On the Horizon:
“The Internet of Things”
Number of Connected Objects Expected to Reach 50bn by 2020
Are we at the Shannon
limit of the Physical Layer?
We don’t know the Shannon
capacity of most wireless channels
 Time-varying channels with no/imperfect CSI
 Channels and networks with feedback
 Channels with delay/energy/HW constraints.
 Channels with interference or relays
 Cellular systems
 Ad-hoc/peer-to-peer networks
 Multicast/common information networks
Rethinking “Cells” in Cellular
Small
Cell
Coop
MIMO
Relay
DAS
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How should cellular
systems be designed?
Will gains in practice be
big or incremental; in
capacity or coverage?
Traditional cellular design “interference-limited”
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MIMO/multiuser detection can remove interference
Cooperating BSs form a MIMO array: what is a cell?
Relays change cell shape and boundaries
Distributed antennas move BS towards cell boundary
Small cells create a cell within a cell
Mobile cooperation via relays, virtual MIMO, network coding.
Are small cells the solution to
increase cellular system capacity?
Yes, with reuse one and adaptive techniques
(Alouini/Goldsmith 1999)
Area Spectral Efficiency
A=.25D2p
 S/I increases with reuse distance (increases link capacity).
 Tradeoff between reuse distance and link spectral efficiency (bps/Hz).
 Area Spectral Efficiency: Ae=SRi/(.25D2p) bps/Hz/Km2.
The Future Cellular Network:
Hierarchical Architecture
Today’s architecture
MACRO:
• 3M Macrocells serving 5 billion users
solving initial • Anticipated 1M small cells per year
coverage issue,
existing network
10x Lower COST/Mbps (?)
PICO: solving
street, enterprise
& home
coverage/capaci
ty issue
10x CAPACITY
Improvement
Macrocell Picocell
Near 100%
COVERAGE
Femtocell
Future systems require Self-Organization (SON) and WiFi Offload
SON Premise and Architecture
Mobile Gateway
Or Cloud
Node
Installation
Self
Healing
SoN
Server
Initial
Measurements
Self
Configurati
on
Measureme
nt
SON
Server
IP Network
Self
Optimization
X2
 SON is part of 3GPP/LTE standard
 Small cells not widely deployed today
X2
Small cell BS
Macrocell BS
X2
X2
SW
Agent
Green” Cellular Networks
Pico/Femto
Coop
MIMO
Relay
DAS
 Minimize
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How should cellular
systems be redesigned
for minimum energy?
Research indicates that
significant savings is possible
energy at both the mobile and base station via
New Infrastuctures: cell size, BS placement, DAS, Picos, relays
New Protocols: Cell Zooming, Coop MIMO, RRM,
Scheduling, Sleeping, Relaying
Low-Power (Green) Radios: Radio Architectures, Modulation,
coding, MIMO
Wifi Networks
Multimedia Everywhere, Without Wires
Wifi is today’s small cell
802.11ac
• Streaming video
• Gbps data rates
• High reliability
• Coverage inside and out
Wireless HDTV
and Gaming
Wireless Local Area
Networks (WLANs)
01011011
0101
1011
Internet
Access
Point
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WLANs connect “local” computers (100m range)
Breaks data into packets
Channel access shared (random access + backoff)
Backbone Internet provides best-effort service
 Poor performance in some apps (e.g. video)
Wireless LAN Standards
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802.11b (Old – 1990s)
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802.11a/g (Middle Age– mid-late 1990s)
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Standard for 2.4GHz ISM band (80 MHz)
Direct sequence spread spectrum (DSSS)
Speeds of 11 Mbps, approx. 500 ft range
Standard for 5GHz band (300 MHz)/also 2.4GHz
OFDM in 20 MHz with adaptive rate/codes
Speeds of 54 Mbps, approx. 100-200 ft range
Many
WLAN
cards
have
(a/b/g/n)
802.11n/ac (Current)
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Standard in 2.4 GHz and 5 GHz band
Adaptive OFDM /MIMO in 20/40/80/160 MHz
Antennas: 2-4, up to 8
Speeds up to 600Mbps/10 Gbps, approx. 200 ft range
Other advances in packetization, antenna use, multiuser MIMO
Why does WiFi performance suck?
Carrier Sense Multiple Access:
if another WiFi signal
detected, random backoff
Collision Detection: if collision
detected, resend
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The WiFi standard lacks good mechanisms to mitigate
interference, especially in dense AP deployments
Multiple access protocol (CSMA/CD) from 1970s
Static channel assignment, power levels, and carrier sensing
thresholds
 In such deployments WiFi systems exhibit poor spectrum
reuse and significant contention among APs and clients
 Result is low throughput and a poor user experience
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Why not use SoN for WiFi?
SoN
Controller
- Channel Selection
- Power Control
- etc.
 SoN-for-WiFi: dynamic self-organization network
software to manage of WiFi APs.
 Allows for capacity/coverage/interference mitigation
tradeoffs.
 Also provides network analytics and planning.
In fact, why not use SoN for all wireless networks?
TV White Space &
Cognitive Radio
mmWave networks
Vehicle networks
Software-Defined Wireless
Network (SDWN) Architecture
Video
Freq.
Allocation
Vehicular
Networks
Security
Power
Control
Self
Healing
ICIC
App layer
M2M
QoS
Opt.
Health
CS
Threshold
SW layer
UNIFIED CONTROL PLANE
HW Layer
WiFi
Cellular
mmWave
Cognitive
Radio
WiGig and mmWave
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WiGig
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Standard operating in 60 GHz band
Data rates of 7-25 Gbps
Bandwidth of around 10 GHz (unregulated)
Range of around 10m (can be extended)
Uses/extends 802.11 MAC Layer
Applications include PC peripherals and displays for
HDTVs, monitors & projectors
mmWave
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Couples 60GHz with massive MIMO and better MAC
Promises long-range communication w/Gbps data rates
Hardware, propagation and system design challenges
Much research on this topic today
Satellite Systems
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Cover very large areas
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Different orbit heights
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Optimized for one-way transmission
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GEOs (39000 Km) versus LEOs (2000 Km)
Radio (XM, Sirius) and movie (SatTV, DVB/S) broadcasts
Most two-way systems went bankrupt
Global Positioning System (GPS) ubiquitous
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Satellite signals used to pinpoint location
Popular in cell phones, PDAs, and navigation devices
IEEE 802.15.4/ZigBee Radios
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Low-Rate WPAN
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Data rates of 20, 40, 250 Kbps
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Support for large mesh networking or star clusters
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Support for low latency devices
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CSMA-CA channel access
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Very low power consumption
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Frequency of operation in ISM bands
Focus is primarily on low power sensor networks
Spectrum Regulation
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Spectrum a scarce public resource, hence allocated
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Spectral allocation in US controlled by FCC
(commercial) or OSM (defense)
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FCC auctions spectral blocks for set applications.
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Some spectrum set aside for universal use
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Worldwide spectrum controlled by ITU-R
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Regulation is a necessary evil.
Innovations in regulation being considered worldwide
in multiple cognitive radio paradigms
Standards
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Interacting systems require standardization
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Companies want their systems adopted as standard
 Alternatively try for de-facto standards
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Standards determined by TIA/CTIA in US
 IEEE standards often adopted
 Process fraught with inefficiencies and conflicts
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Worldwide standards determined by ITU-T
 In Europe, ETSI is equivalent of IEEE
Standards for current systems are summarized in Appendix D.
Emerging Systems*
Cognitive radio networks
 Ad hoc/mesh wireless networks
 Sensor networks
 Distributed control networks
 The smart grid
 Biomedical networks
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*Can have a bonus lecture on this topic late in the quarter if there is interest
Cognitive Radios
CRTx
IP
NCR
NCR
CR
MIMO Cognitive Underlay
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NCRTx
NCRRx
Cognitive Overlay
Cognitive radios support new users in existing
crowded spectrum without degrading licensed users
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CR
CRRx
Utilize advanced communication and DSP techniques
Coupled with novel spectrum allocation policies
Multiple paradigms
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(MIMO) Underlay (interference below a threshold)
Interweave finds/uses unused time/freq/space slots
Overlay (overhears/relays primary message while
cancelling interference it causes to cognitive receiver)
Compressed Sensing in
Communications
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Compressed sensing ideas have found widespread
application in signal processing and other areas
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Basic premise: exploit sparsity to approximate highdimensional system/signal in a few dimensions.
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We ask: how can sparsity be exploited to reduce the
complexity of communication system design
• Sparse signals: e.g. white-space detection
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Sparse samples: e.g. sub-Nyquist sampling
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Sparse users: e.g. reduced-dimension multiuser detection
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Sparse state space: e.g reduced-dimension network control
Ad-Hoc Networks
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Peer-to-peer communications
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No backbone infrastructure or centralized control
Routing can be multihop.
Topology is dynamic.
Fully connected with different link SINRs
Open questions
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Fundamental capacity region
Resource allocation (power, rate, spectrum, etc.)
Routing
Wireless Sensor Networks
Data Collection and Distributed Control
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•
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•
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•
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Smart homes/buildings
Smart structures
Search and rescue
Homeland security
Event detection
Battlefield surveillance
Energy (transmit and processing) is the driving constraint
Data flows to centralized location (joint compression)
Low per-node rates but tens to thousands of nodes
Intelligence is in the network rather than in the devices
Distributed Control over Wireless
Automated Vehicles
- Cars
- Airplanes/UAVs
- Insect flyers
Interdisciplinary design approach
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Control requires fast, accurate, and reliable feedback.
Wireless networks introduce delay and loss
Need reliable networks and robust controllers
Mostly open problems : Many design challenges
The Smart Grid:
Fusion of Sensing, Control, Communications
Open problems:
- Optimize sensor placement in the grid
- New designs for energy routing and distribution
- Develop control strategies to robustify the grid
- Look at electric cars for storage and path planning
carbonmetrics.eu
Applications in Health,
Biomedicine and Neuroscience
Neuro/Bioscience
- EKG signal
Body-Area
Networks
Doctor-on-a-chip
Wireless
Network
reception/modeling
- Brain information theory
- Nerve network
(re)configuration
- Implants to
monitor/generate signals
-In-brain sensor networks
- SP/Comm applied to
bioscience
Recovery from
Nerve Damage
Main Points
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The wireless vision encompasses many exciting systems and
applications
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Technical challenges transcend across all layers of the
system design.
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Existing and emerging systems provide excellent quality for
certain applications but poor interoperability.
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Innovative wireless design needed for mmWave systems,
massive MIMO, SDWN, and Internet of Things connectivity
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Standards and spectral allocation heavily impact the
evolution of wireless technology